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OCR for page 354
For-Profit Enterprise in Health Care. 1986.
National Academy Press, Washington, D.C.
Medicare Patient Outcomes and
Hospital Organizational Mission
Gary Gaumer
The objective of this paper is to examine the
relationship between indicators of quality of
care and ownership status in a large sa~nple of
U. S. hospitals. Very little is known about the
determinants of interhospital differences in pa-
tient outcomes and even less about the rela-
tionship between organizational mission and
patient care. Work by Lust (1980), Scott et al.
(1979), and Bunker et al. (1969) has established
that significant disparities in hospital mortality
rates exist which are, in part, associated with
hospital organizational attributes such as size,
nurse staffing, teaching mission, physician ex-
penence, and administrative span of control.
No studies have yet examined the relationship
between proprietary status and patient out-
comes, nor has the influence of multihospital
system affiliation on outcomes been studied.
This paper examines several types of mea-
sures which, taken together, may be indicative
of differences in patient care practices and
quality of care across groups of hospitals with
differing organizational missions. The mea-
sures we analyze include
~ Post-operative mortality for Medicare
elective surgical admissions measured over
the stay and within 180 days of admission
~ 90-day post-discharge readmission rates
for Medicare elective surgery admissions
· Stabs regarding acccredita~on by Me Joint
Commission on Accreditation of Hospitals
UCAH)
· Two measures of Medicare case mix.
Mr. Gaumer is Vice President of health care re-
search with Abt Associates, Inc., Cambridge, Massa-
chusetts.
354
METHODS
The hospital sample used for our analyses
includes two components:
1. A 25 percent simple random sample of
all continental U.S. hospitals with a median
length of stay of 15 days or less over the 1970-
1978 period
2. All other similarly defined short-term
hospitals in the 15 states with prospective pay-
ment programs. ~
The surgical admissions we studied included
inguinal hernia repair, hysterectomy, chole-
cystectomy, he m orrhoide ctomy , op en pro s -
tatectomy, transurethral resection of prostate,
excision of bladder lesion, and mastectomy.
Patient data were taken from the Health Care
Financing Administration's (HCFA) MED-
PAR file, containing clinical and billing data
on Medicare inpatient stays for 20 percent of
Medicare beneficiaries. Data were gathered
for the 1974-1981 period on each sample hos-
pital. Table 1 shows the resultant sample sizes.
Table 2 shows characteristics of sample hos-
pitals.
Constructing measures of readmission rates
and post-discharge fatality rates required spe-
cial processing of the HCFA files. A 90-day
readmission indicator (0, 1) was created for
each study patient by scanning the entire
MEDPAR file across years to see if patients
discharged fiom study hospitals were read-
mitted to any hospitals within 90 days of the
date of discharge. For 180-day post-admission
death rates, a similar process was used, except
that HCFA's Medicare eligibility files were
used to determine if beneficiary death oc-
curred within 180 days of the admission.
Unpublished accreditation data were ob-
tained from JCAH. Status codes were obtained
that reflect full (2- or 3-year) accreditation and
OCR for page 355
355
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OCR for page 356
356
FOR-PROFIT ENTERPRISE IN HEALTH CARE
TABLE 2 Characteristics of Sample Hospitals,a 1981 Data
Proprie- Non
Proprie- tary Non-profit
tary Inde- profitsInde
VariableChain pendent Chainpendent
Number of hospitals in
sample107 117 4351,310
Average number of
beds staffed148 103 199185
Minimum40 11 158
Maximum638 400 872969
Average Medicare
case-mix index1.00 0.97 1.02102
Minimum0.79 0.71 0.720.56
Maximum1.20 1.22 1.391.75
Percent fully JCAH
accreditedC0.79 0.50 0.740.55
Percent covered by
state prospective
payment program0.17 0.44 0.570.64
Percent located in
SMSAd0.78 0.68 0.610.60
County Characteristics
(unweighted mean)
Percent population on
AFDCe3.9 4.3 4.24.2
Births per 100,000
population1,675 1,568 1,6581,506
Per capita income8,756 8,540 8,3078,423
Percent population
with health
insurance75.5 81.5 82.287.2
Percent population on
Medicare11.5 12.8 13.013.4
Number of hospital
beds per 100,000
population537 638 787770
M.D.s per 100,000
population161 153 144145
Percent M.D.s who
are specialists0.81 0.75 0.710.75
HMO penetration rate0.065 0.041 0.0380.035
Percent population
white0.80 0.81 0.880.89
Median years of
education11.9 11.S 11.911.9
Unemployment rate7.2 7.3 7.67.7
-
aExcludes government hospitals and members ofthe Council of Teathing Hos-
pitals.
bAmerican Hospital Association data for 1981-1982 were used to assign this
ownership status indicating membership in a multibospital system.
CJoint Commission on Accreditation of Hospitals.
Standard metropolitan statistical area.
eAid to Families with Dependent Children.
OCR for page 357
MEDICARE PATIENT OUTCOMES
TABLE 3 Unadjusted In-Hospital Mortality Rates by Hospital Type
Proprietary Propnetary Nonprofita Nonprofit
Chain Independent Chain Independent
All eight elective procedures
1975 0.010 0.013 0.012 0.013
1977 0.009 0.009 0.014 0.012
1979 0.010 0.007 0.011 0.011
1981 0.011 0.004 0.011 0.012
1981 by procedure
Hemorrhoidectomy 0.000 0.000 0.000 0.004
Cholecystectomy 0.042 0.014 0.032 0.032
Inguinal hernia 0.004 0.004 0.006 0.004
Open prostatectomy 0.000 0.000 0.014 0.015
Transurethral resection of
prostate 0.009 0.000 0.009 0.010
Hysterectomy 0.000 0.013 0.002 0.006
Excision of bladder lesion 0.000 0.000 0.010 0.012
Mastectomy 0.000 0.012 0.015 0.006
aAmencan Hospital Association data for 1981-1982 were used to assign this ownership
status indicating membership in a multihospital system.
only 1-year accreditation as a result of the sur-
vey. For analytic purposes, we used an indi-
cator of whether the hospital was fully (2- or
3-year) accredited or not. 2
Medicare case-mix data for 1981 were coded
from the September 30, 1983 Federal Regis-
ter.
357
Several measures of organizational mission
were developed from AMA's annual survey
designation of proprietary status. An indicator
of affiliation with a proprietary hospital system
was coded Tom 1974-1981 annual directories
of He Federation of American Hospitals. AMA's
1982 annual survey data were used to deter
TABLE 4 Unadjusted 180-Day Mortality Rates by Hospital Type
_ . . .
Proprietary Proprietary Nonprofita Nonprofit
Chain Independent Chain Independent
All eight elective procedures
1975 0.049 0.045 0.050 0.013
1977 0.063 0.057 0.058 0.012
1979 0.062 0.070 0.054 0.011
1981 0.055 0.041 0.056 0.054
1981 by procedure
Hemorrhoidectomy 0.020 0.000 0.029 0.025
Cholecystectomy 0.059 0.067 0.083 0.076
Inguinal hernia 0.027 0 043 0.029 0.026
Open prostatectomy 0.051 0.032 0.055 0.040
Transurethral resection of
prostate 0.077 0.041 0.063 0.064
Hysterectomy 0.000 0.026 0.019 0.019
Excision of bladder lesion 0.095 0.039 0.083 0.095
Mastectomy 0.033 0.037 0.047 0.037
aAmencan Hospital Association data for 1981-1982 were used to assign this ownership
status indicating membership in a muldhospital system.
OCR for page 358
358
mine if the hospital was a member of a mul-
tihospital system. Using these data, for-profit
affiliations were available for all hospital years,
but nonprofit chain affiliation was only cap-
tured at one point in time.
DESCRIPTIVE STATISTICS
Tables 3, 4, and 5 contain means on patient
outcome measures.3 The unadjusted outcome
data often show large differences across types
of ownership, and considerable instability over
time no doubt arising, in part, from the rel-
atively small samples of patients for some pro-
cedure groups.
Mortality During the Stay
For the aggregate of eight elective proce-
dures, death rates averaged about 1.1 percent.
No significant trends are apparent. Death rates
generally appear lower in proprietary hospi-
tals, particularly in the independent investor-
owned hospitals. Post-operative death rates are
often zero for procedures such as open pros-
tatectomy and excision of bladder lesion. Mor-
tality rates for the specific procedures show
the instability in measures that arises from in-
frequent deaths and relatively small samples.
FOR-PROFIT ENTERPRISE IN HEALTH CARE
Mortality Rates Within 180 Days of
Admission
Six-month mortality rates average about 5
percent for all elective surgery, often some-
what lower in proprietary hospitals. No trends
are apparent. Among the specific procedures,
bladder lesions and gall bladder removals have
highest death rates. Patterns of mortality by
hospital organizational types are very incon-
sistent across the specific procedures.
Readmission Rates Within 90 Days of
Discharge
Readmission rates for the eight procedures
are about 9 percent. There is a slight upward
trend in these rates. Readmission rates show
similar performance of nonprofit and proprie-
taries, although on balance, mean rates for
proprietaries are slightly higher. Readmission
rates are low for hernia repair, hysterectomy,
and mastectomy, and highest for procedures
relating to the bladder and prostate.
The descriptive data suggest that it may not
be meaningful to statistically examine many of
the specific procedures separately due to the
combined consequences of rare outcomes and
small samples of cases for particular ownership
TABLE 5 Unadjustec! 90-Day Readmission Rates by Hospital Type
Proprietary Proprietary NonprofitQ Nonprofit
Chain Independent Chain Independent
All eight elective procedures
1975 0.067 0.083 0.084 0.081
1977 0.104 0.101 0.103 0.094
1979 0.088 0.093 0.084 0.083
1981 0.111 0.089 0.093 0.089
1981 by procedure
Hemorrhoidectomy 0.140 0.056 0.079 0.073
Cholecystectomy 0.083 0.072 0.092 0.087
Inguinal hernia 0.077 0.075 0.058 0.052
Open prostatectomy 0.098 0.081 0.110 0.081
Transurethral resection of
prostate 0.136 0.129 0.115 0.113
Hysterectomy 0.063 0.013 0.057 0.064
Excision of bladder lesion 0.190 0.099 0.114 0.139
Mastectomy 0.076 0.063 0.076 0.047
America Hospital Association data for 1981-1982 were used to assign this ownership
status indicating membership in a multihospital system.
OCR for page 359
MEDICARE PATIENT OUTCOMES
categories. We examined standardized out-
comes for the following types of procedures:
· All elective procedures taken together
· Cholecystectomy
· Hernia repair
· Transurethral resection of prostate.
Figures 1, 2, 3, and 4 show farther detail
on the unadjusted patient outcome rates for
these four procedure categones. Data on length
of stay are also included for reference pur-
poses. All tables show means weighted by
number of admissions in the particular surgical
category. Ike tables show four bed-size cat-
egories.
Size of Hospital
Patient outcomes for elective procedures
seem to vary systematically with respect to
hospital size. Larger hospitals have longer
lengths of stay, higherin-hospitalfatality rates,
and lower readmission rates. Inguinal hernia
repair is the only exception, where no pattern
in readmission rates is apparent. The pattern
is different for mortality rates within 180 days
of admission, generally, the fatality rates are
much lower for very small hospitals. Chole-
cystectomy is an exception, where no size pat-
tern is seen.
Medicare Case Mix
Hospitals were classified on the basis of the
HCFA-published 1981 Medicare diagnosis-re-
lated group (DRG) case-mix index. As with
size, patterns are evident in He raw data.
Readmission patterns are quite uniform, hos-
pitals with a more complex (costly) Medicare
case mix have lower readmission rates and
shorter lengths of stay for these elective pro-
cedures. Mortality rate patterns are not so uni-
form. Excepting cholestectomy, the in-hospital
and 180~day mortality rates are generally higher
in hospitals with higher case-m~x values. No
pattern is evident for cholecystectomy.
Organization of Hospital
Looking first at differences between pro
359
prietary and voluntary hospitals, the weighted
means show that proprietary hospitals have
comparable or lower mortality rates. In-hos-
pital mortality rates are lower for all eight pro-
cedures taken together (.008 compared to .012)
and for transurethral resection of the prostate
(.004 compared to .0101. Proprietary hospitals
have lower 180-day mortality rates for all eight
procedures together (.049 compared to .055)
and for cholecystectomy (.061 versus .076~. The
only observed instance where proprietary hos-
pitals have much higher mortality is hernia
repair, where 180-day post-admission mortal-
ity is 3. 7 percent compared to 2.7 percent for
nonprofit hospitals. Readmission rates are gen-
erally much higher in proprietary hospitals,
excepting cholecystectomy, where the reverse
is true. Length-o£stay differences are nonex-
istent or quite small, though for the aggregate
of eight procedures and prostate surgery the
proprietary hospitals have slightly lower lengths
of stay.
When subgroups of investor-owned hospi-
tals are compared to their voluntary chain and
nonchain counterparts, some patterns emerge.
Independent proprietary hospitals have the
lowest values on both mortality rate measures
of all four groups of hospitals except for cho-
lecystectomy; for this procedure, in-hospital
fatality rates are equal to their voluntary coun-
terparts and 180-day mortality is higher than
in other types of hospitals. Readmission rates
and length of stay for independent proprie-
taries are generally equal to or higher than for
independent voluntary hospitals. The excep-
tion is hernia repair, where independent pro-
prietary hospitals have the lowest readmission
rate.
The pattern for proprietary chains is similar;
for readmission rates, proprietary chains have
higher rates than voluntary chains, except for
hernia repair. But unlike the independent pro-
prietaries, the investor-owned chain hospitals
have lower lengths of stay than the voluntary
chain hospitals. For chain hospitals there is no
pattern whatsoever for mortality rates across
procedure categones; for the aggregate of eight
procedures, proprietary chains have mortality
rates about equal to those observed in vol-
untary chain hospitals.
OCR for page 360
360
6.0
5.0
4.0
3.0
1.2
1.0
id
~ 0.8
111
0.6
0.4
12.0
.0.0
8.0
6.0
9
con
7
75- 200
200 400 400+
SIZE (beds)
i
FIGURE 1 Eight elective procedures, 1981 data
FOR-PROFIT ENTERI'RISE IN HEALTH CARE
180 Day Mortality
Mortality During Stay
Hi
_ ~
_ ~ l
it,
Readmission
J;
ength of Stay (live discharges)
.9- Not
.9 1.1 1.1 + For
M ED ICAR E
CASEM IX
Profit
For
Profit
~1
Chn Ind Chn Ind
Propr Volun
ORGANIZATION
OCR for page 361
MEDICARE: PATIENT OUTCOMES
9.0
8.0
Z 7.0
UJ
6.0
5.0
4.0
4.5
4.0
3.5
3.0
c:
cry
LU
2.5
2.0
t.5
1.0
16.0
14.0
z 12.0
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cr:
us
10.0
8.0
6.0
16
14
12
10
180 Day Mortality
I.
Mortality During Stay
Readmission
.N
L
Length of Stay (live discharges) ~
75- 200- .9- Not For Chn Ind Chn Ind
<75 200 400 400+ .9 1.1 1.1+ For Profit Propr Volun
Profit
SIZE (beds) MEDICARE ORGANIZATION
CASEM iX
FIGURE 2 Cholecystectomy outcomes, 1981 data.
361
OCR for page 362
362
FOR-PROFIT ENTERTRISE IN HEALTH CARE
8.0
7.D
Be
c.' 6.0
LL
5.0
4.0
1 .0
0.8
0.6
LL
0.4
0.2
o
16.0
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of
C: 12.0
G
10.0
8.0
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10
180 Day Mortality
i/
~ .
Mortality During Stay
. ~
Readmission
_ .
l ~
Length of Stay (live discharges)
75- 200- 9- Not For Chn Ind Chn Ind
<~75 200400 400+ .9 1.1 1.1t For Profit Propr Volun
Profit
SIZE (beds) MEDICARE ORGANIZATION
CASEM IX
FIGURE 3 Inguinal hernia repair, 1981 data.
OCR for page 363
MEDICARE PATIENT OUTCOMES
8.0
7.0
z
Cal 6.0
G
UJ
C~ 5.0
4.0
1.0
0.8
0.6
0.4
0.2
o
16.0
'_ 14.0
at
up
~ 12.0
cr
10.0
8.0
12
In
6 10
SIZE (beds) MEDICARE
CASEM I X
FIGURE 4 Transurethral resection of prostate, 1981 data.
363
180 Day Mortality
~ l
OCR for page 364
364
Accreditation Trends
The trends in accreditation status have not
been pronounced, although there are clear dif-
ferences across groups of hospitals. Table 6 and
Figure 5 show the unadjusted data on hill ICAH
accreditation rates (percent finely accredited).
There is a clear demarcation between chain
and nonchain hospitals, but little difference
between proprietary and nonprofit indepen-
dents. For the chain affiliates, about 65 to 75
percent of hospitals maintain full accredita-
tion. For independents, hill accreditation rates
in 1981 were 50 to 55 percent, with the pro-
prietaries up from 40 percent in the early 1970s.
Table 6 also shows the specific accreditation
status of hospital years being studied. Lower
accreditation rates for proprietary indepen-
dents are apparently due to lower rates of par-
ticipation in the ICAH program.
STATISTICAL RESULTS
Mortality During the Stay
Table 7 shows the results of statistical tests
on the ratio of actual to expected death rates
FOR-PROFIT ENTERPRISE IN HEALTH CARE
at discharge. 4 The table shows various differ-
ences of interest (rows) for each of the aggre-
gate and individual elective procedures
(columns). If probability is less than 0.10 the
coefficient is reported which, because of the
log form, is interpreted as the difference be-
tween the indicated groups of hospitals ex-
pressed in percentage terms (e.g., mortality
rates are x percent higher in the first-listed
group of hospitals than in the other). If the
coefficient was not significant (p <.lO), only
the direction of differences is reported. For
example, the first cell in the table (.119) in-
dicates that chain-~liated hospitals have in-
hospital mortality rates for all elective proce-
dures combined that are ll.9 percent higher
than for nonchain hospitals, ret par.
The dominant conclusion Tom these tests is
that hospital ownership may not be a strong
or consistent imBuence on postoperative mor-
tality rates; significant results are not propa-
gated across all procedures categories. The data
are not without patterns, Cough they may fail
to be fillly persistent; proprietary status is De-
quently found to be associated with lower in-
hospital mortality, and chain affiliation is oRen
associated with higher mortality. There is no
TABLE 6 Trends in Accreditation by the loins Commission on
Accreditation of Hospitals UCAH)
Percent with 2-Year Accreditationa
Proprietary Proprietary Nonprofitb Nonprofit
Year Chain Independent Chain Independent
1974 0.660 0.399 0.724 0.605
1975 0.688 0.387 0.679 0.586
1976 0.649 0.400 0.623 0.505
1977 0.688 0.399 0.640 0.514
1978 0.729 0.415 0.662 0.492
1979 0.663 0.398 0.710 0.522
1980 0.676 0.496 0.730 0.547
1981 0.785 0.496 0.736 0.547
Accreditation Status: All Years Contained
Percent full 69 42
Percent provisional 10 10
Percent other 21 48
69 54
14 12
18 34
aThe balance of hospitals either did not seek ICAH accreditation, had status
of unaccredited, or were accredited for only 1 year.
bAmerican Hospital Association data for 1981-1982 were used to assign this
ownership status for nonprofits, indicating membership in a multihospital system.
OCR for page 365
MEDICARE PATIENT OUTCOMES
0.7
0.6
0.5
OA
0.3
FIGURE 5 Accreditation trends by hospital status.
significant evidence that proprietary chains are
significantly different from other ~ror~rietarv
hospitals.
We are concerned that the pattern (higher
mortality in chains; lower mortality in pro-
prietaries) may be confounded with severity.
Although mortality rates were standardized for
the age/sex/co-morbid status and covariates
provide control for aggregate case-mix and size
differences, we still worry that the differences
in mortality may be partially due to severity
differences which are not captured in our stan-
dardization approach. In part, our concern
stems from the pattern of case-mix results be-
low showing that proprietary hospitals may
have a less complex case mix.
180-Day Post-Admission Mortality
The statistical results for tests on this mea-
sure generally tend to be the reverse of those
found for in-hospital mortality, though usually
less consistent. Compared to voluntary hos-
pitals, chain hospitals are not consistently dif-
ferent from their independent counterparts,
though they have significantly lower mortality
rates for prostate surgery. Investor-owned
hospitals have higher 180-day mortality rates,
though these differences are statistically sig-
nificant only in the hernia repair and prostate
models. The effect of switching to proprietary
status is measured directly as Test 3; here we
find no significant differences to support the
365
~ 0.8 _
G
Z 0.7 _ -__
o
0.6 _ - - _
o: ^ ' _
Cry
if:
I
Cal
J
J
LL
Proprietary
-_ _
I_
Independent Proprietary
_ _ ~
Nonprofit Chain
_ _
Nonprofit Independent ~
1 1 1 1
1974 1975 1976 1977 1978
YEAR
1979 1980 1981
pattern of higher 180-day mortality in inves-
tor-owned hospitals.
Results are also inconsistent on the differ-
ences between independent proprietary hos-
pitals and their chain-affiliated counterparts.
There is some indication that switching from
independent to chain status is associated with
lower 180-day mortality rates; this pattern is
statistically significant for the aggregate of eight
procedures, and the signs are consistent for
the other procedure-specific tests.
90-Day Readmission Rates
The readmission tests in Table 7 show only
one consistent pattern. Chain affiliates are of-
ten found to have higher readmission rates.
There is also some evidence that proprietary
chains have higher readmission rates than other
proprietary hospitals.
Accreditation Rates
Table 8 shows the statistical results for ac-
creditation rates. The likelihood of hill (2-year)
accreditation with JCAH is consistently re-
lated to the organizational measures; no doubt
this reflects, in part, mission and image dif-
ferences which differentially affect the pro-
pensities of hospitals to seek JCAH
accreditation. All the tested models show that
chain-a~liated hospitals are more often ac
OCR for page 366
Inhospital mortality
Chain vs. independent
Proprietary vs. voluntary
Switch from voluntary to
proprietary
Proprietary chain vs.
proprietary independent
Switch from proprietary
independent to
proprietary chain
180-day mortality
Chain vs. independent
Proprietary vs. voluntary
Switch from voluntary to
proprietary
Proprietary chain vs.
proprietary independent
Switch from proprietary
independent to
proprietary chain
90-day readmission rate
Chain vs. independent
Proprietary vs. voluntary
Switch from voluntary to
proprietary
Proprietary chain vs.
+
-.248 (.099)
proprietary independent .204 (.057)
Switch from proprietary
independent to
proprietary chain
-
366
FOR-PROFIT ENTERPRISE IN HEALTH CARE
TABLE 7 Statistical Results on Patient Outcomes: Percentage Differences in Adverse
Outcome Ratea (p value in parentheses)
Test Statistic
All Eight
Electives Cholecystectomy
Inguinal
Hernia
Repair
Transurethral
Resection
of Prostate
.119 (.033) 120 (.033)
-.401 (.000)
+
+
+
+
. 124 (.056) -
-.181 (.096)
+
.181 (.002)
.172 (.001) .171 (.000)
+ _
+
.197 (.0~01) +
+
+
-.420 (.024)
.873 (.035) .764 (.063) +
.157 (.062)
aDependent variable is natural log of ratio of actual to expected rate. Only coefficients with p <.10 are shown
(p value in parentheses). Positive values indicate higher adverse outcome rates in the first-listed category of
hospital.
credited than others. Results also indicate that,
after standardization, proprietary chains have
significantly higher accreditation rates than
other investor-owned hospitals. Both models
that test the effect of switching status show
similar patterns, though differences are not
statistically significant.
Case Mix
Case-mix differences were examined by
means of two measures made on Medicare ad
missions. One measure, available only for 1981,
is the Medicare case-mix index based on ICD9
DRGs which was developed for the Tax Equity
and Fiscal Responsibility Act (TEFRA). The
other measure is the expected 180-day post-
admission mortality rate for the aggregate of
Medicare elective surgery cases.5 The former
measure is a form of resource use index; the
latter is a measure of severity or prognosis.
Results are not Filly consistent, though gen-
erally both measures show that proprietary
hospitals have a simpler case mix than others,
cet par.
OCR for page 367
MEDICARE PATIENT OUTCOMES
TABLE 8 Statistical Results for Accreditation and Case Mix
Percentage Dilierence*
Expected 180-Day
Full Accredi- Mortality for 1981 Medicare
tation Rate Elective Surgery Case-Mix Index
Chain versus
independent
Proprietary versus
voluntary
Switch from voluntary
to proprietary
Proprietary chain
versus proprietary
.087 (.~) +
-.114 (.000)
independent .170 (.000)
Switch from
proprietary
independent to
proprietary chain
+
-.001 (.078) -.019 (.001)
NA
+
HA
*Coefficients are interpreted as the percentage difference between the indi-
cated groups. Only coefficients with p <.10 are shown.
SUMMARY AND DISCUSSION
Findings on Investor-Owned Hospitals
The analysis of quality-of-care indicators
provides no evidence for concluding that the
profit motive, in the aggregate, has compro-
mised patient care to the point of causing large
and systematic differences in post-operative
mortality or readmission. Results indicate that
Medicare post-operative mortality rates are of-
ten lower in proprietary hospitals, after stan-
dar~li~ing for patient age, sex, and co-morbidity;
and controlling for interhospital differences in
hospital size and other hospital and market
characteristics. This pattern does not persist
for mortality rates within 180 days of admis-
sion; proprietary hospitals have somewhat
higher mortality rates although they are not
sufficiently higher than the levels in voluntary
hospitals to be considered statistically sig,nifi-
cant. The findings on readmission rates admit
to no pattern whatsoever again providing no
support for the view that investor-owned hos-
pitals have poorer patient outcomes. In sum,
the patient outcome findings do not show any
persisting pattern that would support a con-
clusion that proprietary hospitals are providing
poorer quality of care.
367
Analysis of accreditation status with JCAH
shows that proprietaries are consistently less
likely to be fully (2-year) accredited. Whether
this finding has a bearing on quality of care is,
of course, problematic due to the nature ofthe
ICAH survey and the fact that the accredita-
tion program is voluntary. The data indicate
that lower rates of participation in the ICAH
program are largely responsible for the lower
rates of full accreditation, implying that the
statistical findings may have little or no bearing
on the quality of the patient care process in
investor-owned hospitals.
Findings on Chain Sequences for
l~vestor-Owned Hospitals
There is very inconsistent evidence on the
issue of how proprietary chains may be dis-
tinctive from independent proprietaries in
teens of quality indicators. No significant dif-
ferences or pattern of results is seen when
mortality rates are compared directly. Switch-
ing from independent to chain affiliation is
wealdy associated with higher in-hospital mor-
tality and lower 180-day mortality. Patterns in
readmission differences are not seen. JCAH
accreditation rates are also found to be more
favorable in proprietary chains than in other
OCR for page 368
368
investor-owned hospitals. Finally, chain affil-
iation is associated with more complex case
mix.
These results are, without question, not a
conclusive test on the issue of quality of care.
Aside from the usual caveats about correla-
tional analysis and a nonrandomized design
and imperfect indicators of quality, we are con-
cerned about several statistical issues. Deaths
(and even readmissions) are relatively rare
events for elective surgery. Given small sam-
ple sizes per hospital, we observe fairly ex-
treme variability in our measures. While the
use of weighted least squares and the conti-
nuity correction factor will tend to minimize
this problem, we still observe quite "noisy"
data tending to make it less likely to reject
the null hypothesis. That is, differences be-
tween groups need to be quite large before it
is likely that they are considered statistically
significant. While we use a liberal critical con-
fidence limit (p<0. 10), it still appears that in-
tergroup differences in outcome rates smaller
than 10 to 12 percent or so are not detectable.
The sample size issue is most germane to
consideration of the use of the results stem-
ming from the four-way design. This difficulty
is unfortunate because this approach essen-
tially allows each hospital to be its own control,
which is a strong hedge against confounding
stemming from omitted determinants of out-
comes that are unique to individual hospitals.
The number of hospitals that switch status is
quite small. Estimates of the ejects of switch-
ing from proprietary independent to propne-
tary chain status are based on about 1.2 percent
of the sample of hospital years (N = 15,422
in total). Estimates of the effects of switching
to proprietary status (versus nonprofit) are based
on only about 3.7 percent of the sample, where
such switches occur. Consequently, the re-
sults of the four-way model tests are not likely
to be reliable.
FOR-PROFIT ENTERPRISE IN HEALTH CARE
lbe figure to detect persistent patterns may,
in part, derive from these statistical power
considerations. We can conclude, however, that
no apparent pattern of large ownership differ-
ences exist for serious patient outcomes fol-
lowing elective surgery.
NOTES
These states are Anzona, Colorado, Connecticut,
Indiana, Kentucky, Maryland, Massachusetts, Min-
nesota, Nebraska, New Jersey, New York, Pennsyl-
vania (western), Rhode Island, Washington, and
Wisconsin.
2We followed Dowling et al. (1976) who reported
that separating 1-year from full accreditation status of-
fers a more sensitive measure of accreditation status.
3Hospi~1 year means have been weighed by number
of admissions in specific surgical categories.
4The ratio of actual to expected outcomes is used to
standardize outcomes for interhospital differences in
patient age, sex, and co-morbid status. Appendix A
describes the standardization approach as well as other
aspects of the statistical method.
Appendix B contains the full results of the statistical
models that are summarized in this section.
sThese rates are developed on the basis of patient
age, sex, procedure, and existence (or not) of a second
diagnosis on admission.
REFERENCES
Bunker, J., W. Forrest, F. Mosteller, and L. Vandam,
eds. (1969) The National Halothane Study, National
Institute of General Medical Sciences, Bethesda, Md.
Dowling, William et al. (1976) The Evaluation of
Blue Cross in Medicaid Prospective Reimbursement
Systems in Downstate New York. Final Report, DHEW
Contract HEW-OS-74-248.
Lust, H. (1980) The relationship between surgical
volume and mortality: An exploration of causal factors
and alternative models. Medical Care, 18~9), Septem-
ber.
Scott, W., B. Flood, and W. Ewy (1979) Organiza-
tional determinants of services, quality, and cost of care
in hospitals, Mudbank Memorial Fund Quarterly, 57~2~.
OCR for page 369
APPENDIX A
Statistical Methods
CONTROLLING FOR SEVERITY
A principal analytic issue in evaluating in-
terhospital differences is controlling for prog-
nosis or expected outcome on admission. Our
approach was to adjust or normalize the mea-
sured outcome rate for factors known to affect
prognosis. The ratio of the measured outcome
to the expected outcome provides a measure
of seventy-adjusted outcomes for a given hos-
pital year.
These "expected" rates are the cell means
on each outcome measure (fatality and read-
mission rates) for a 20 percent sample of Med-
icare admissions patients in all years (1974-
1981) from a 25 percent random sample of short-
term U. S. hospitals. The 96 cells were defined
by procedure (eight categories), age (three cat-
egories 65-74, 75-84, over 84), sex (two cate-
gories), and presence of a second diagnosis
(two categories). Two sets of norms (means)
were used: 1974-1978 and 1979-1981. This was
done to acknowledge the shift to ICD9-CM
coding on Medicare files which began in 1979.
After the patient file for each year was scored
with appropriate means, both the actual and
"expected" outcome rates were computed for
each hospital year observation by summing
across patients and dividing by the number of
cases.
SPECIFYING OWNERS H I ~ MEASURES
Three basic forms of ownership influence
were examined in the study. The first two
specify the ownership influence within the twos
way or treatment-control design:
Model 1: Prop (= 1 if proprietary, 0 other-
wise), and
Chain (= 1 if member of chain, 0
otherwise)
Model 2: Prop (= 1 if proprietary, 0 other-
wise), and
Chain (= 1 if member of chain, 0
otherwise), and
Prochain (= 1 if proprietary chain,
O otherwise)
The coefficients on the organization mea-
sures in the Model 1 specification tests for
differences between chain and nonchain hos-
pitals and between proprietary and nonpro-
prietary hospitals. In Mode} 2, the coefficient
on the Prochain variable tests whether pro-
prietary chain hospitals are different from other
proprietary hospitals. Both models test for dif-
ferences in means between groups of hospitals
(e. g., proprietary versus other), controlling for
differences in means between groups on other
covariates we include.
A third specification uses a different test:
measuring the difference between groups in
their pre/post change. This four-way (pre/post-
treatment/control) design reduces the risk that
unmeasured baseline differences between the
groups of institutions are confounding the re-
sults. This design is intrinsically preferable to
the treatment control approach used in the first
two models, but supers here due to several
factors: the small number of hospitals that ac-
tually change status (between profit and non-
profit and between chain and independent)
over the study period; and the inability to gather
tine series data on nonprofit chain affiliation.
Hence, the hypothesis test
Ho: (Qpos~ - Qpre)PnOPR
(Qpos' Qpre)NONPROP = 0
is highly leveraged on those few cases where
ownership status changed. We do test this ap-
proach, aclmowledging the problem, allowing
the results to be considered by the reader as
part of the overall pattern of findings. The
specification is
Mode! 3: Prop (see other), and
DProchain (see other), and
DChain (= 1 if ever chain affili-
ated)i
Prop (= 1 in years when proprie-
tary, 0 otherwise), and
DProp (= 1 if ever proprietary), and
369
OCR for page 370
370
Chain (= 1 for years when affiliated
with a chain))
In Mocle} 4, the coefficient on Prop tests
whether the change to proprietary status in-
fluenced outcomes. The coefficient on Pro-
chain in Model 3 tests whether a change from
an independent proprietary to a chain-affili-
ated proprietary influenced the outcomes.
COVARL\TES
The characteristics of hospitals in various
ownership groups of interest are different. Of
course, without random assignment this prob-
lem of noncomparability is always a problem,
precluding simple hypothesis tests of cli$er-
ences in means. We use a multivanate (regres-
sion) approach to standardize groups for
differences in many of these hospital charac-
teristics. Table 2 presents descriptive data on
the values of covariates across ownership
groups. In addition to those measures shown
in the table, the regression models include
covariate as
· Whether binding review by a professional
standards review organization (PSRO) was
conducted in the hospital for the year
· Whether the hospital was subject to state
certificate-of-need (CON) authority for each
year
· Percentage increase in the CPI for the
SMSA
· County population
· County population per square mile
· A set of year-specific, dummy (0,1) vari-
ables
· A set of region-specific dummy variables
· Number of staffed beds following Luft
(1980~. This measure captures scale effects on
outcomes.
ESTIMATION
For the patient outcome analyses, a weighted
regression (OLS) was used to estimate the basic
models. This is done to remove heteroscedas-
tic (systematic) variances in residuals across
hospital year observations which, if uncor-
rected, make all parameter estimates ineffi-
cient (though unbiased). These patterns are
likely in our model because our hospital year
FOR-PROFIT ENTERPRISE IN HEALTH CARE
outcome measures are based on samples of
patients of widely varying sizes, and while the
20 percent sample Is probably random, the
variances of these estimates are likely to be
systematically related to the number of cases
in each hospital year on which the mean was
computed.
CONTINUITY CORRECTION FACTOR
Another estimation problem is that, for some
measures, we can expect to observe a cluster
of zeros for outpatient outcome variables. With
small samples per hospital year, for example,
it is plausible that no deaths or readmissions
will be observed even though some cases were
admitted. The number of zeros in the data
approaches 50 percent for some types of elec-
tive surgery. Consequently, we observe a bi-
modal distribution on our measures. The
approach for dealing with the clusters of cases
at zero (and at high extreme values) is the use
of a "continuity correction factor." This ap-
proach is a standard technique for smoothing
the "ends" of a distribution on abmary variable
(e.g., values approaching 0 and values ap-
proachir~g 17.2
SIGNIFICANCE LEVELS
In all statistical analyses we report coeffi-
cients that are significant at the p = .10 level
or better (two-tailed test). There are No rea-
sons for reporting at a level of significance
somewhat lower than the p = .05 that is cus-
tomary in the literature. First, we are con-
cerned that measurement errors in the
MEDPAR file may elevate the standard errors
in the morlel, causing significant differences
to be overlooked if tolerance levels are too
stringent. Second, we believe that the policy
applications of this work require that we allow
less than the usual chance of committing false
negative (type II) elTors (ignoring an adverse
difference because a critical significance level
is too stringent).
NOTES
ZAHA data for 1981-1982 were used to assign this
ownership status for nonprofits indicating membership
in a multihospital system.
OCR for page 371
MEDICARE PATIENT OUTCOMES
2 Following techniques suggested by Cox (1970) and
Bishop et al. (1975), we can use an adjustment of the
form:
Ai + 1/6
~ = Ni + 113
where Ai = the observed number of adverse outcomes
for the hospital year; Ni = the number of cases; and
= the adjusted adverse outcome rate. The constants
(1/6, 1/3), which define the value of this Taylor expan-
sion on n are suggested by Mosteller and Tukey (1977).
The choice remains somewhat arbitrary, though larger
fractions tend to have more dramatic "smoothing" ef-
fects.
APPENDIX B
Mode! Results
371
REFERENCES
Bishop Y., S. Fienberg, and P. Holland (1975) Dis-
crete Multivariate Analysis. Cambridge, Mass.: MIT
Press.
Cox, D. R. (1970) Analysis of Binary Data. London:
Chapman and Hall.
Luff, H. (1980) The relationship between surgical
volume and mortality. Medical Care 18, September.
Mosteller, F., and J. Tukey (1977) Data Analysis and
Regression. Reading, Mass.: Addison Wesley.
TABLE B-1 Statistical Results on Post-Operative Mortality Rates: Percentage Difference
in Mortality Rate During the Staya
Surgical Category
Model
All Elective Inguinal
Surgery Cholecystectomy Hernia Repair
Transurethral Resection
of Prostate
Model 1
Chainb
Proprietary
Model 2
Chain
Proprietary
Prochaind
Model 3
DChaine
Prochain
Proprietary
Model 4
DProprietaryf
Proprietary
Chain
O. 119 (0.033) 0.120 (0.033)
-0.401 (0.000)
0.124 (0.056)
- - 0.181 (0.096)
0.129 (0.023) 0.116 (0.031) +
+
-
-0.274 (0.035) -
+
0.129 (0.032) 0.121 (0.032) ~
-
t
a Dependent variable is natural log of ratio of actual to expected mortality rate at discharge. Only coefficients
with p <.10 are shown (p value in parentheses).
b Chain = 1 if chain affiliated in year.
Proprietary = 1 if proprietary in year.
dProchain = 1 if proprietary and chain.
eDChain = 1 for all years if ever chain affiliated.
fDProprietary = 1 for all years if ever proprietary.
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372
FOR-PROFIT ENTERPRISE IN HEALTH CARE
TABLE B-2 Statistical Results on Readmission Rate: Percentage Difference in
Readmission Ratea
Surgical Category
All Elective
Surgery Cholecystectomy
Model
Inguinal Transurethral Resection
Hernia Repair of Prostate
Mastectomy
Model 1
Chamb
Proprietary
Model 2
Chain
Proprietary
Prochain~
Model 3
DChaine
Prochain
Proprietary
Model 4
+
0.204 (0.057)
-
DProprietaryJ
Proprietary
Chain
0.197 (0.001)
+
0.2~ (0.000)
0.268 (0.045)
- - 0.420 (0.024)
- 1. 167 (0.004)
0.873 (0.035)
-1.176 (0.004)
0.764 (0.063)
0.382 (0.000)
+
aDependent variable is natural log of ratio of actual to expected rate. Only coefficients with p
(p value in parentheses).
bChain = 1 if chain affiliated in year.
Proprietary = 1 if proprietary in year.
Prochain = 1 if proprietary and chain.
eDChain = 1 for all years if ever chain affiliated.
fD proprietary = 1 for all years if ever proprietary.
<.10 are shown
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MEDICARE PATIENT OUTCOMES
TABLE B-3 Statistic Results on 180-Day Morbid Rate: Percentage Deference in
Mortality Ratea
.
373
Surgical Category
All Elective Inguinal Transurethral Resection
Model Surgery Cholecystectomy Hernia Repair of Prostate
~.
Mastectomy
Model 1
Chainb - + + - 0.081 (0.002)
PropnetaryC + ~0.172 (0.001) 0.171 (0.000)
Model 2
Chain - + + -0.089 (0.001)
Proprietary + + 0.141 (0.004) +
Prochaind - + + 0.157 (0.062)
Model 3
DChaine + ~0.116 (0.021) - 0.430 (0.033)
Prochain -0.248 (0.099) - - -
Proprietary + + 0.116 (0.021) +
Model 4
DPropnetaryf + + 0.337 (0.035) +
Proprietary + +
Chain - + + -0.081 (0.002)
a Dependent variable is natural log of ratio of acutal to expected rate. Only coefficients with p <.10 are shown
(p value in parentheses).
bChain = 1 if chain affiliated in year.
Proprietary = 1 if proprietary in year.
dProchain = 1 if proprietary and chain.
eDChain = 1 for all years if ever chain affiliated.
fDProprietary = 1 for all years if ever proprietary.
OCR for page 374
374
FOR-PROFIT ENTERPRISE IN HEALTH CARE
TA;BLE B-4 Statistical Results on Case Mix and SCAM
Measuresa
lCAH Status
(1 = 2 Year, O
Otherwise
Expected 180-Day
Mortality Rate for
All Elective
Surgeries
1981 Medicare
Case-Mix Index
Model 1
Chain0.087 (0.000)
Proprietary-0.114 (0.000)
- 0.001 (0.078) - 0.019 (0.001)
Model 2
Chain0.066 (0.000) + +
Proprietary-0.177 (0.000) - -0.024 (0.001)
Prochain0.170 (0.000) - +
Model 3
Proprietary
DChain
DProchain
Model 4
D Proprietary
Proprietary
Chain
- O. 182 (0.000)
0.199 (0.000)
+
-0.085 (0.008)
0.088 (o.ooo) +
NA
NA
_ . .
aCoefFicients indicate differences for the indicated group expressed in per-
centage terms: numbers in parentheses are p values.
bModels of the Joint Commission on Accreditation of Hospitals UCAH) used
ordinary least-squares estimation.
Representative terms from entire chapter:
readmission rates
